图书馆系统读者图书偏好分析

TEM Journal Pub Date : 2024-02-27 DOI:10.18421/tem131-44
Zhi-Yao Foo, Kok-Why Ng, S. Haw, E. Anaam
{"title":"图书馆系统读者图书偏好分析","authors":"Zhi-Yao Foo, Kok-Why Ng, S. Haw, E. Anaam","doi":"10.18421/tem131-44","DOIUrl":null,"url":null,"abstract":"Library is a place that contains various resources and materials. Many invaluable knowledge can be found in the library. By analysing the library’s data, it is possible to obtain information that can further improve its services. This research aims to extract information from Multimedia University (MMU) library and present insightful visualization of the information to enhance the library administration. At present, the library does not have information on the book preferences of the library users. The book preferences statistics can be relatively helpful as the library will know what books can be imported in the future. By doing so, more people will visit the library and they will have more related books to use as reference or to read. In addition, there are no existing dashboards to display information on all borrowers, no visitor. In the absence of this, this research adopts the data science methodology to determine the book preferences of library users by using machine learning techniques such as clustering and classification. Lastly, a dashboard will be developed to display all the findings which includes statistics on the visitors and book preferences.","PeriodicalId":515899,"journal":{"name":"TEM Journal","volume":"49 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Book Preferences Among Visitors in Library System\",\"authors\":\"Zhi-Yao Foo, Kok-Why Ng, S. Haw, E. Anaam\",\"doi\":\"10.18421/tem131-44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Library is a place that contains various resources and materials. Many invaluable knowledge can be found in the library. By analysing the library’s data, it is possible to obtain information that can further improve its services. This research aims to extract information from Multimedia University (MMU) library and present insightful visualization of the information to enhance the library administration. At present, the library does not have information on the book preferences of the library users. The book preferences statistics can be relatively helpful as the library will know what books can be imported in the future. By doing so, more people will visit the library and they will have more related books to use as reference or to read. In addition, there are no existing dashboards to display information on all borrowers, no visitor. In the absence of this, this research adopts the data science methodology to determine the book preferences of library users by using machine learning techniques such as clustering and classification. Lastly, a dashboard will be developed to display all the findings which includes statistics on the visitors and book preferences.\",\"PeriodicalId\":515899,\"journal\":{\"name\":\"TEM Journal\",\"volume\":\"49 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TEM Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18421/tem131-44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TEM Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18421/tem131-44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

图书馆是一个藏有各种资源和资料的地方。许多宝贵的知识都可以在图书馆找到。通过分析图书馆的数据,可以获得进一步改善其服务的信息。本研究旨在提取多媒体大学(MMU)图书馆的信息,并对信息进行深入的可视化展示,以提高图书馆的管理水平。目前,图书馆没有关于图书馆用户图书偏好的信息。图书偏好统计可以帮助图书馆了解今后可以引进哪些图书。这样,就会有更多的人访问图书馆,他们也会有更多的相关书籍作为参考或阅读。此外,目前还没有仪表板来显示所有借阅者的信息,也没有访客的信息。鉴于此,本研究采用数据科学方法,通过聚类和分类等机器学习技术来确定图书馆用户的图书偏好。最后,将开发一个仪表板来显示所有研究结果,其中包括访客和图书偏好的统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Book Preferences Among Visitors in Library System
Library is a place that contains various resources and materials. Many invaluable knowledge can be found in the library. By analysing the library’s data, it is possible to obtain information that can further improve its services. This research aims to extract information from Multimedia University (MMU) library and present insightful visualization of the information to enhance the library administration. At present, the library does not have information on the book preferences of the library users. The book preferences statistics can be relatively helpful as the library will know what books can be imported in the future. By doing so, more people will visit the library and they will have more related books to use as reference or to read. In addition, there are no existing dashboards to display information on all borrowers, no visitor. In the absence of this, this research adopts the data science methodology to determine the book preferences of library users by using machine learning techniques such as clustering and classification. Lastly, a dashboard will be developed to display all the findings which includes statistics on the visitors and book preferences.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信